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Cirrascale Cloud Services Announces Availability of SambaNova’s Dataflow-as-a-Service on Cirrascale AI Innovation Cloud

Cirrascale Cloud Services Announces Availability of SambaNova’s Dataflow-as-a-Service on Cirrascale AI Innovation Cloud

Cirrascale Cloud Services, a provider of deep learning infrastructure solutions for autonomous vehicle, Natural Language Processing (NLP) and computer vision workflows, announced that it is partnering with SambaNova Systems to offer Dataflow-as-a-Service as part of its AI Innovation Cloud platform. Dataflow-as-a-Service is a fully-integrated Foundation Model Platform that delivers pre-trained deep learning and Foundation Models that deliver value to enterprises 22x faster.

“We’ve been working hard to be an innovation accelerator company that our customers can rely on to deliver the absolute best AI solutions in the cloud,” said David Driggers, CTO, Cirrascale Cloud Services. “Expanding our cloud platform to include SambaNova brings us closer than ever to being a one-stop-shop for customers to gain access to the latest, state-of-the-art large language models, such as GPT-175B and true-resolution computer vision.”

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“Dataflow-as-a-Service enables customers to deploy the most advanced pre-trained deep learning and Foundation Models in days. Customers have been asking us for this solution; we’re delighted to announce that it’s available today,” stated Matt Taylor, VP of Strategic Sales and Partnerships, SambaNova Systems. “Each model is pre-trained, reducing the need for heavy investment and deployment time, and can be fine-tuned within an organization’s environment to deliver world record accuracy.”

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SambaNova Dataflow-as-a-Service is a fully integrated platform that delivers production-ready, pre-trained foundation models that can be further adapted through fine-tuning or pre-training to deliver world record accuracy. This enables organizations to quickly deploy state-of-the-art capabilities while avoiding the complexity, financial investment, and time necessary to fully train these models internally. The solution also provides an efficient, scalable approach to large language and computer vision, accessed through simple APIs for ease of use.

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